scholarly journals Constraining a System of Interacting Parameterizations through Multiple-Parameter Evaluation: Tracing a Compensating Error between Cloud Vertical Structure and Cloud Overlap

2013 ◽  
Vol 26 (17) ◽  
pp. 6698-6715 ◽  
Author(s):  
R. A. J. Neggers ◽  
A. P. Siebesma
Keyword(s):  
Radiative Transfer ◽  
General Circulation ◽  
Surface Energy Budget ◽  
Time Range ◽  
Soil System ◽  
Cloud Structure ◽  
Column Model ◽  
Single Column ◽  
Single Column Model ◽  
The Impact

Abstract This study explores the opportunities created by subjecting a system of interacting fast-acting parameterizations to long-term single-column model evaluation against multiple independent measurements at a permanent meteorological site. It is argued that constraining the system at multiple key points facilitates the tracing and identification of compensating errors between individual parametric components. The extended time range of the evaluation helps to enhance the statistical significance and representativeness of the single-column model result, which facilitates the attribution of model behavior as diagnosed in a general circulation model to its subgrid parameterizations. At the same time, the high model transparency and computational efficiency typical of single-column modeling is preserved. The method is illustrated by investigating the impact of a model change in the Regional Atmospheric Climate Model (RACMO) on the representation of the coupled boundary layer–soil system at the Cabauw meteorological site in the Netherlands. A set of 12 relevant variables is defined that covers all involved processes, including cloud structure and amplitude, radiative transfer, the surface energy budget, and the thermodynamic state of the soil and various heights of the lower atmosphere. These variables are either routinely measured at the Cabauw site or are obtained from continuous large-eddy simulation at that site. This 12-point check proves effective in revealing the existence of a compensating error between cloud structure and radiative transfer, residing in the cloud overlap assumption. In this exercise, the application of conditional sampling proves a valuable tool in establishing which cloud regime exhibits the biggest impact.

scholarly journals Continuous Single-Column Model Evaluation at a Permanent Meteorological Supersite

2012 ◽  
Vol 93 (9) ◽  
pp. 1389-1400 ◽  
Author(s):  
R. A. J. Neggers ◽  
A. P. Siebesma ◽  
T. Heus
Keyword(s):  
Case Studies ◽  
General Circulation ◽  
Column Model ◽  
Parameterization Schemes ◽  
Numerical Predictions ◽  
Single Column ◽  
Weather And Climate ◽  
Single Column Model ◽  
Process Level

Uncertainties in numerical predictions of weather and climate are often linked to the representation of unresolved processes that act relatively quickly compared to the resolved general circulation. These processes include turbulence, convection, clouds, and radiation. Single-column model (SCM) simulation of idealized cases and the subsequent evaluation against large-eddy simulation (LES) results has become an often used and relied on method to obtain insight at process level into the behavior of such parameterization schemes; benefits of SCM simulation are the enhanced model transparency and the high computational efficiency. Although this approach has achieved demonstrable success, some shortcomings have been identified; among these, i) the statistical significance and relevance of single idealized case studies might be questioned and ii) the use of observational datasets has been relatively limited. A recently initiated project named the Royal Netherlands Meteorological Institute (KNMI) Parameterization Testbed (KPT) is part of a general move toward a more statistically significant process-level evaluation, with the purpose of optimizing the identification of problems in general circulation models that are related to parameterization schemes. The main strategy of KPT is to apply continuous long-term SCM simulation and LES at various permanent meteorological sites, in combination with comprehensive evaluation against observations at multiple time scales. We argue that this strategy enables the reproduction of typical long-term mean behavior of fast physics in large-scale models, but it still preserves the benefits of single-case studies (such as model transparency). This facilitates the tracing and understanding of errors in parameterization schemes, which should eventually lead to a reduction of related uncertainties in numerical predictions of weather and climate.

scholarly journals The E3SM version 1 single-column model

2020 ◽  
Vol 13 (9) ◽  
pp. 4443-4458
Author(s):  
Peter A. Bogenschutz ◽  
Shuaiqi Tang ◽  
Peter M. Caldwell ◽  
Shaocheng Xie ◽  
Wuyin Lin ◽  
...  
Keyword(s):  
General Circulation ◽  
Model Development ◽  
Circulation Model ◽  
System Model ◽  
Earth System ◽  
Efficient Tool ◽  
Column Model ◽  
Community Atmosphere Model ◽  
Single Column ◽  
Single Column Model

Abstract. The single-column model (SCM) functionality of the Energy Exascale Earth System Model version 1 (E3SMv1) is described in this paper. The E3SM SCM was adopted from the SCM used in the Community Atmosphere Model (CAM) but has evolved significantly since then. We describe changes made to the aerosol specification in the SCM, idealizations, and developments made so that the SCM uses the same dynamical core as the full general circulation model (GCM) component. Based on these changes, we describe and demonstrate the seamless capability to “replay” a GCM column using the SCM. We give an overview of the E3SM case library and briefly describe which cases may serve as useful proxies for replicating and investigate some long-standing biases in the full GCM runs while demonstrating that the E3SM SCM is an efficient tool for both model development and evaluation.

scholarly journals Introduction of prognostic rain in ECHAM5: design and single column model simulations

2008 ◽  
Vol 8 (11) ◽  
pp. 2949-2963 ◽  
Author(s):  
R. Posselt ◽  
U. Lohmann
Keyword(s):  
General Circulation ◽  
Large Scale ◽  
Circulation Model ◽  
Cloud Microphysics ◽  
Rain Water ◽  
Time Step ◽  
Surface Precipitation ◽  
Column Model ◽  
Single Column ◽  
Single Column Model

Abstract. Prognostic equations for the rain mass mixing ratio and the rain drop number concentration are introduced into the large-scale cloud microphysics parameterization of the ECHAM5 general circulation model (ECHAM5-PROG). To this end, a rain flux from one level to the next with the appropriate fall speed is introduced. This maintains rain water in the atmosphere to be available for the next time step. Rain formation in ECHAM5-PROG is, therefore, less dependent on the autoconversion rate than the standard ECHAM5 but shifts the emphasis towards the accretion rates in accordance with observations. ECHAM5-PROG is tested and evaluated with Single Column Model (SCM) simulations for two cases: the marine stratocumulus study EPIC (October 2001) and the continental mid-latitude ARM Cloud IOP (shallow frontal cloud case – March 2000). In case of heavy precipitation events, the prognostic equations for rain hardly affect the amount and timing of precipitation at the surface in different SCM simulations because heavy rain depends mainly on the large-scale forcing. In case of thin, drizzling clouds (i.e., stratocumulus), surface precipitation is sensitive to the number of sub-time steps used in the prognostic rain scheme. Cloud microphysical quantities, such as cloud liquid and rain water within the atmosphere, are sensitive to the number of sub-time steps in both considered cases. This results from the decreasing autoconversion rate and increasing accretion rate.

scholarly journals Introduction of prognostic rain in ECHAM5: design and Single Column Model simulations

2007 ◽  
Vol 7 (5) ◽  
pp. 14675-14706 ◽  
Author(s):  
R. Posselt ◽  
U. Lohmann
Keyword(s):  
General Circulation ◽  
Large Scale ◽  
Circulation Model ◽  
Cloud Microphysics ◽  
Rain Water ◽  
Time Step ◽  
Surface Precipitation ◽  
Column Model ◽  
Single Column ◽  
Single Column Model

Abstract. Prognostic equations for the rain mass mixing ratio and the rain drop number concentration are introduced into the large-scale cloud microphysics parameterization of the ECHAM5 general circulation model (ECHAM5-RAIN). For this a rain flux from one level to the next with the appropriate fall speed is introduced. This maintains rain water in the atmosphere to be available for the next time step. Rain formation in ECHAM5-RAIN is, therefore, less dependent on the autoconversion rate than the standard ECHAM5 but shifts the emphasis towards the accretion rates in accordance with observations. ECHAM5-RAIN is tested and evaluated with two cases: the continental mid-latitude ARM Cloud IOP (shallow frontal cloud case – March 2000) and EPIC (a marine stratocumulus study – October 2001). The prognostic equations for rain hardly affect the amount and timing of precipitation at the surface in different Single Column Model (SCM) simulations for heavy precipitating clouds because heavy rain depends mainly on the large-scale forcing. In case of thin, drizzling clouds (i.e., stratocumulus), an increase in surface precipitation is caused by more sub-time steps used in the prognostic rain scheme until convergence is reached. Cloud microphysical quantities, such as liquid and rain water, are more sensitive to the number of sub-time steps for light precipitation. This results from the decreasing autoconversion rate and increasing accretion rate.

scholarly journals Decomposing the Drivers of Polar Amplification with a Single Column Model

2020 ◽  
pp. 1-33
Author(s):  
Matthew Henry ◽  
Timothy M. Merlis ◽  
Nicholas J. Lutsko ◽  
Brian E.J. Rose
Keyword(s):  
General Circulation ◽  
Energy Transport ◽  
Circulation Model ◽  
Lapse Rate ◽  
Arctic Amplification ◽  
Polar Surface ◽  
Surface Warming ◽  
Column Model ◽  
Single Column ◽  
Single Column Model

AbstractThe precise mechanisms driving Arctic amplification are still under debate. Previous attribution methods compute the vertically-uniform temperature change required to balance the top-of-atmosphere energy imbalance caused by each forcing and feedback, with any departures from vertically-uniform warming collected into the lapse-rate feedback. We propose an alternative attribution method using a single column model that accounts for the forcing-dependence of high latitude lapse-rate changes. We examine this method in an idealized General Circulation Model (GCM), finding that, even though the column-integrated carbon dioxide (CO2) forcing and water vapor feedback are stronger in the tropics, they contribute to polar-amplified surface warming as they produce bottom-heavy warming in high latitudes. A separation of atmospheric temperature changes into local and remote contributors shows that, in the absence of polar surface forcing (e.g., sea-ice retreat), changes in energy transport are primarily responsible for the polar amplified pattern of warming. The addition of surface forcing substantially increases polar surface warming and reduces the contribution of atmospheric dry static energy transport to the warming. This physically-based attribution method can be applied to comprehensive GCMs to provide a clearer view of the mechanisms behind Arctic amplification.

scholarly journals The E3SM version 1 Single Column Model

2020 ◽  
Author(s):  
Peter A. Bogenschutz ◽  
Shuaiqi Tang ◽  
Peter M. Caldwell ◽  
Shaocheng Xie ◽  
Wuyin Lin ◽  
...  
Keyword(s):  
General Circulation ◽  
Model Development ◽  
Circulation Model ◽  
System Model ◽  
Earth System ◽  
Efficient Tool ◽  
Column Model ◽  
Community Atmosphere Model ◽  
Single Column ◽  
Single Column Model

Abstract. The single column model (SCM) functionality of the Energy Exascale Earth System Model version 1 (E3SMv1) is described in this paper. The E3SM SCM was adopted from the SCM used in the Community Atmosphere Model (CAM), but has evolved significantly since then. We describe changes made to the aerosol specification in the SCM, idealizations, and developments made so that the SCM uses the same dynamical core as the full general circulation model (GCM) component. Based on these changes, we describe and demonstrate the seamless capability to ``replay" a GCM column using the SCM. We give an overview of the E3SM case library and briefly describe which cases may serve as useful proxies for replicating and investigate some long standing biases in the full GCM runs, while demonstrating that the E3SM SCM is an efficient tool for both model development and evaluation.

scholarly journals A statistical subgrid-scale algorithm for precipitation formation in stratiform clouds in the ECHAM5 single column model

2011 ◽  
Vol 11 (3) ◽  
pp. 9335-9374 ◽  
Author(s):  
S. Jess ◽  
P. Spichtinger ◽  
U. Lohmann
Keyword(s):  
Cloud Cover ◽  
Climate Model ◽  
Global Climate Model ◽  
Subgrid Scale ◽  
Column Model ◽  
Microphysical Properties ◽  
Single Column ◽  
Single Column Model ◽  
The Impact ◽  
Precipitation Formation

Abstract. Cloud properties are usually assumed to be homogeneous within the cloudy part of the grid-box, i.e. subgrid-scale inhomogeneities in cloud cover and/or microphysical properties are often neglected. However, precipitation formation is initiated by large particles. Thus mean values are not representative and could lead to a delayed onset of precipitation. For a more physical description of the subgrid-scale structure of clouds we introduce a new statistical sub-column algorithm to study the impact of cloud inhomogeneities on stratiform precipitation. Each model column is divided into N independent sub-columns with sub-boxes in each layer, which are completely clear or cloudy. The cloud cover is distributed over the sub-columns depending on the diagnosed cloud fraction. Mass and number concentrations of cloud droplets and ice crystals are distributed randomly over the cloudy sub-columns according to prescribed probability distributions. Shapes and standard deviations of the distributions are obtained from aircraft observations. We have implemented this sub-column algorithm into the ECHAM5 global climate model to take subgrid variability of cloud cover and microphysical properties into account. Simulations with the Single Column Model version of ECHAM5 were carried out for one period of the Mixed-Phase Polar Arctic Cloud Experiment (MPACE) campaign as well as for the Eastern Pacific Investigation of climate Processes (EPIC) campaign. Results with the new algorithm show an earlier onset of precipitation for the EPIC campaign and a higher conversion of liquid to ice for the MPACE campaign, which reduces the liquid water path in better agreement with the observations than the original version of the ECHAM5 model.

scholarly journals Large-Eddy Simulation and Single-Column Modeling of Thermally Stratified Wind Turbine Arrays for Fully Developed, Stationary Atmospheric Conditions

2015 ◽  
Vol 32 (6) ◽  
pp. 1144-1162 ◽  
Author(s):  
Adrian Sescu ◽  
Charles Meneveau
Keyword(s):  
Thermal Stratification ◽  
Layer Structure ◽  
Potential Temperature ◽  
Surface Fluxes ◽  
Heat Fluxes ◽  
Shear Stresses ◽  
Column Model ◽  
Large Eddy ◽  
Single Column ◽  
Single Column Model

AbstractEffects of atmospheric thermal stratification on the asymptotic behavior of very large wind farms are studied using large-eddy simulations (LES) and a single-column model for vertical distributions of horizontally averaged field variables. To facilitate comparisons between LES and column modeling based on Monin–Obukhov similarity theory, the LES are performed under idealized conditions of statistical stationarity in time and fully developed conditions in space. A suite of simulations are performed for different thermal stratification levels and the results are used to evaluate horizontally averaged vertical profiles of velocity, potential temperature, vertical turbulent momentum, and heat flux. Both LES and the model show that the stratification significantly affects the atmospheric boundary layer structure, its height, and the surface fluxes. However, the effects of the wind farm on surface heat fluxes are found to be relatively small in both LES and the single-column model. The surface fluxes are the result of two opposing trends: an increase of mixing in wakes and a decrease in mixing in the region below the turbines due to reduced momentum fluxes there for neutral and unstable cases, or relatively unchanged shear stresses below the turbines in the stable cases. For the considered cases, the balance of these trends yields a slight increase in surface flux magnitude for the stable and near-neutral unstable cases, and a very small decrease in flux magnitude for the strongly unstable cases. Moreover, thermal stratification is found to have a negligible effect on the roughness scale as deduced from the single-column model, consistent with the expectations of separation of scale.

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